Prediction Models May Improve Early Identification of Psoriatic Arthritis in Patients With Psoriasis
Researchers have developed and internally validated prediction models designed to identify patients with psoriasis at increased risk for psoriatic arthritis (PsA), with the goal of supporting earlier referral and disease detection.
Because PsA is frequently underdiagnosed and delayed diagnosis is associated with poorer outcomes, investigators sought to identify predictors present at psoriasis onset and create models for both concurrent and future PsA risk.
The analysis used data from the Stockholm Psoriasis Cohort, a Swedish inception cohort that enrolled patients within 1 year of their first psoriasis lesion between 2001 and 2005. Among 628 participants without self-reported PsA at enrollment, 83 patients (13%) were found to have concomitant PsA.
Investigators developed 2 referral models, 1 incorporating laboratory biomarkers and 1 without, as well as 2 prognostic models predicting subclinical PsA over 3-year and 15-year time horizons. Recursive partitioning and penalized regression techniques were used to generate the models.
The referral model incorporating biomarkers stratified patients into 4 risk groups using 5 variables: arthralgia, fatigue, psoriasis phenotype, high-sensitivity C-reactive protein, and psoriasis disease activity. The estimated probability of concomitant PsA ranged from 1% to 62% across these groups.
The prognostic models demonstrated good overall performance. Optimism-adjusted area under the curve values ranged from 0.76 to 0.84, with reasonable calibration. Based on clinician-derived risk thresholds, the models showed positive net benefit for referral and monitoring decisions, although they appeared less useful for selecting candidates for preventive treatment.Pain, HLA-B27 positivity, and systemic inflammation emerged as the strongest predictors of future PsA development.
According to the authors, “predictors of psoriatic arthritis are already present at psoriasis onset.” They conclude that the models “could support clinical decision-making,” while emphasizing that external validation is required before clinical implementation.
Reference
Svedbom A, Mallbris L, Zabotti A, et al. Predicting psoriatic arthritis in new-onset psoriasis: development of multivariable prediction models from an inception cohort study. Lancet Rheumatol. 2026;S2665-9913(26)00115-3. doi:10.1016/S2665-9913(26)00115-3
